Emergency managers need access to the right data to effectively and efficiently plan for and respond to disasters. Social media offers a data source that is increasingly relevant for disaster management, but emergency response organizations typically lack capacity to monitor and mine social media data at scale. One remedy is to pair human volunteers, who label relevant information, with computers to train and update artificial intelligence (AI) systems for scalable monitoring. Including local volunteers in the process is important because they are uniquely capable of identifying locally-relevant images, text, and conversations that reflect their communities. Yet, we currently have no mechanism to systematically pair these human volunteer/AI-systems with emergency management organizations. Therefore, the fundamental issue this project investigates is the feasibility of leveraging the strengths of local members of a Community Emergency Response Team (CERT) with AI—called human-AI teaming—to bridge this gap. The unique CIVIC aspect of this project is to leverage existing collaborations with a CERT organization to assess the feasibility. The long-term vision is to develop a sustainable, replicable, and empirically informed framework for integrating CERT volunteers into the automated processing of social media data using an AI-based system. The project supports education and diversity by providing research experiences to diverse students, as well as training CERT volunteers in social media and human-AI teaming. Findings can help emergency managers better train their volunteers who comb through social media using understandings of the built environment to help machines see new patterns in data. Hence, this project supports NSF's mission to promote the progress of science and advance the nation's health, prosperity, and welfare by demonstrating the value of leveraging local CERT volunteers, in partnership with emergency managers, to generate disaster situation awareness.

The goal of this planning grant is to analyze existing human-AI teaming disaster data and involve civic partners in focus groups to better understand the attitudes and beliefs of CERT volunteers, emergency managers, key governmental organizations, and non-governmental organizations. This project will develop deep knowledge of digital volunteer teams, how they work, how to motivate them, and how to have them support the objectives of emergency managers. Thus, we advance theory around volunteer teaming in the technology space and human-in-the-loop protocols. This project provides meaningful ways for more citizens to participate in disaster planning and response, and develops a training curriculum for CERT volunteers who work with social media data in an effort to build sustainable volunteer efforts.

This project is in response to Track B - CIVIC Innovation Challenge - Resilience to Natural Disasters a collaboration with NSF and the Department of Homeland Security.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
2043522
Program Officer
Linda Bushnell
Project Start
Project End
Budget Start
2021-01-15
Budget End
2021-06-30
Support Year
Fiscal Year
2020
Total Cost
$49,855
Indirect Cost
Name
University of Texas Austin
Department
Type
DUNS #
City
Austin
State
TX
Country
United States
Zip Code
78759